Increasing the efficiency of scheduled and unscheduled computing tasks

ABSTRACT

One or more processors determine that a user is attempting to execute an unscheduled computing task and estimate the time for execution. One or more processors determine that a computing task is scheduled to execute along with the unscheduled computing task. One or more processors warn the user that the computing task is scheduled to execute along with the unscheduled computing task. One or more processors estimate one or both of: a utilization of processing and a memory consumption for the computing tasks and determine whether a threshold will be exceeded. If the threshold will be exceeded, one or more processors warn the user.

BACKGROUND OF THE INVENTION

The present invention relates generally to the field of computerefficiency, and more particularly to helping a computer user increasecomputer efficiency.

Many tasks scheduled on calendar programs require certain amounts ofprocessing, memory and execution time. For example, scheduled meetingswhere screen sharing occurs require computing resources. Screen sharingis often used to accomplish tasks such as viewing runtime reports, whichalso require CPU utilization and memory consumption. Other schedulabletasks that consume computing resources include, for example, virtualtraining.

Executing two or more computing tasks simultaneously often results inpoor computing performance. Poor computing performance can manifestitself as slow computing or even program malfunctions, such as freezingand crashing. In general, overloading a computer CPU and memory is oftenharmful to the computer and wastes time.

SUMMARY

Embodiments of the present invention provide a method, system, andprogram product to facilitate computer efficiency. One or moreprocessors determine that a user is attempting to execute an unscheduledcomputing task. One or more processors estimate a length of time ofexecution for the unscheduled computing task. One or more processorsdetermine that a scheduled computing task is scheduled to execute whilethe unscheduled computing task is executing, wherein the scheduledcomputing task is scheduled to be executed automatically or manually andthe scheduled computing task occurs during one or more of: an eventscheduled in a calendar program, a software update, and a computerbackup. One or more processors warn the user that the unscheduledcomputing task will be executing when the scheduled computing taskbegins executing. One or more processors estimate one or both of: autilization of processing and a memory consumption for one or both of:the unscheduled computing task and the scheduled computing task. One ormore processors determine whether the one or both of: the utilization ofprocessing and the memory consumption for the one or both of: theunscheduled computing task and the scheduled computing task exceed athreshold. In response to a determination that the threshold will beexceeded, one or more processors warn the user that the threshold willbe exceeded. One or more processors analyze at least one of theunscheduled computing task and the scheduled computing task for one ormore first identifying attributes. One or more processors search adatabase for one or more stored computing tasks that have one or moresecond identifying attributes. One or more processors identify apredictive correlation between at least one of the one or more firstidentifying attributes and at least one of the one or more secondidentifying attributes, wherein the predictive correlation allows anestimate to be made of one or more of: the utilization of processing andthe memory consumption and wherein the one or more first identifyingattributes and the one or more second identifying attributes include oneor more of: a file size, a file type, and a program language used, andthe length of time of execution for one or both of: the unscheduledcomputing task and the scheduled computing task.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a computing efficiencyenvironment, in accordance with an exemplary embodiment of the presentinvention.

FIG. 2 illustrates operational processes for increasing computingefficiency, in accordance with an exemplary embodiment of the presentinvention.

FIG. 3 illustrates a first part of operational processes for estimatingcomputing resource consumption by a computing efficiency program, inaccordance with an exemplary embodiment of the present invention.

FIG. 4 illustrates a second part of operational processes for estimatingcomputing resource consumption by a computing efficiency program, inaccordance with an exemplary embodiment of the present invention.

FIG. 5 depicts a block diagram of components of the computing deviceexecuting a computing efficiency program, in accordance with anexemplary embodiment of the present invention.

DETAILED DESCRIPTION

Computing tasks that require CPU utilization and memory consumption areoften scheduled using, for example, a calendar application. Often thesescheduled computing tasks, which are executed either manually orautomatically, compete against other unscheduled computing tasks thatalso require computer resources. If CPU- and memory-intensive computingtasks compete against each other at the same time, computer sluggishnessand malfunctions often occur.

Scheduled computing tasks are executed at known future times, unlikenon-scheduled computing tasks. Thus, a thoughtful user may elect topostpone the execution of an unscheduled computing task if he or sheknows that a scheduled computing task will be executing at the sametime. Unfortunately, scheduled computing tasks are often initiated whileunscheduled computing tasks are executing because, for example, a userdid not know how long the unscheduled computing task would take or theuser was not thinking about the scheduled computing task when he or sheinitiated the unscheduled computing task.

Embodiments of the present invention recognize that executing multiplecomputing tasks at the same time on a computing device is often lessefficient than executing the multiple computing tasks separately.Embodiments of the present invention provide a method, computer programproduct, and computer system that estimates the amount of processing andmemory a given computing task will consume along with an estimate of thelength of time of execution, i.e., execution time. Embodiments of thepresent invention provide a method, computer program product, andcomputer system to warn a user when an unscheduled computing task willlikely execute at the same time as a scheduled computing task.

The present invention will now be described in detail with reference tothe Figures.

FIG. 1 is a functional block diagram illustrating a computing efficiencyenvironment, generally designated 100, in accordance with one embodimentof the present invention. Computing efficiency environment 100 includescomputing device 102 connected over network 112. Computing device 102includes computing efficiency program 104, scheduled computing task 106,unscheduled computing task 108, and database 110.

In various embodiments of the present invention, computing device 102 isa computing device that can be a standalone device, a server, a laptopcomputer, a tablet computer, a netbook computer, a personal computer(PC), or a desktop computer. In another embodiment, computing device 102represents a computing system utilizing clustered computers andcomponents to act as a single pool of seamless resources. In general,computing device 102 can be any computing device or a combination ofdevices with access to scheduled computing task 106, unscheduledcomputing task 108, and database 110 and is capable of executingcomputing efficiency program 104. Computing device 102 may includeinternal and external hardware components, as depicted and described infurther detail with respect to FIG. 5.

In this exemplary embodiment, computing efficiency program 104,scheduled computing task 106, unscheduled computing task 108, anddatabase 110 are stored on computing device 102. However, in otherembodiments, computing efficiency program 104, scheduled computing task106, unscheduled computing task 108, and database 110 may be storedexternally and accessed through a communication network, such as network112. Network 112 can be, for example, a local area network (LAN), a widearea network (WAN) such as the Internet, or a combination of the two,and may include wired, wireless, fiber optic or any other connectionknown in the art. In general, network 112 can be any combination ofconnections and protocols that will support communications betweencomputing device 102, computing efficiency program 104, scheduledcomputing task 106, unscheduled computing task 108, and database 110, inaccordance with a desired embodiment of the present invention.

In exemplary embodiments, computing efficiency program 104 warns a userinitiating an unscheduled computing task (such as unscheduled computingtask 108) that the unscheduled computing task will likely overlap with ascheduled computing task (such as scheduled computing task 106), therebycreating a situation of unsatisfactory computing performance. Theoperational processes used by computing efficiency program 104 aredescribed in more detail in FIGS. 2 and 3.

In exemplary embodiments, scheduled computing task 106 is any scheduledcomputing task that utilizes computer resources that include one or moreCPUs and memory. For example, scheduled computing task 106 is a taskexecuted during a scheduled meeting such as an internet meetinginvolving screen sharing. Scheduled computing task 106 is also ascheduled task such as a virtual training event. Scheduled computingtask 106 also includes tasks such as file back-up events that areregularly scheduled.

In exemplary embodiments, unscheduled computing task 108 is anycomputing task that is about to be executed by a user, which utilizescomputer resources that include one or more CPUs and memory. Bothunscheduled computing task 108 and scheduled computing task 106 arecomputing tasks that compete for processing and memory on computingdevice 102 or other remote computing devices.

In exemplary embodiments, database 110 contains data enabling computingefficiency program 104 to estimate one or more of: the level of CPUutilization, memory consumption, and execution time (i.e., “parameters”)for one or both of: scheduled computing task 106 and unscheduledcomputing task 108. Database 110 is also a repository for data stored bycomputing efficiency program 104, the data including one or more of: thelevel of CPU utilization, memory consumption, and execution time for oneor both of: scheduled computing task 106 and unscheduled computing task108. This latter data is used by computing efficiency program toestimate parameters for future scheduled and unscheduled computingtasks.

FIG. 2 illustrates operational processes, generally designated 200, forincreasing computing efficiency, in accordance with an exemplaryembodiment of the present invention.

In step 202, computing efficiency program 104 determines that a user isattempting to execute unscheduled computing task 108 on computing device102. In various embodiments, unscheduled computing task 108 is anycomputing task that, when executing, requires one or both of: CPUutilization and memory consumption. In some embodiments, openingsoftware such as a word processor, spreadsheet, graphics program, etc.constitutes an unscheduled computing task such as unscheduled computingtask 108. In other embodiments, unscheduled computing task 108 alsoincludes the execution of software. For example, executing a report orany other program code are unscheduled computing tasks such asunscheduled computing task 108.

In step 204, computing efficiency program 104 estimates the length oftime of execution (i.e., execution time or runtime) of unscheduledcomputing task 108. In various embodiments, computing efficiency program104 estimates the execution time of unscheduled computing task 108 bysearching for computing tasks that are substantially similar in database110 where the substantially similar computing tasks have known executiontimes. The operational processes involved in computing efficiencyprogram 104 estimations of the unscheduled computing task 108 executiontime are discussed in more detail in FIG. 3.

In step 206, computing efficiency program 104 checks for one or morescheduled computing tasks such as scheduled computing task 106, whichare scheduled to execute during the execution of unscheduled computingtask 108 if the user initiates unscheduled computing task 108 at thecurrent time. Scheduled computing tasks such as scheduled computing task106 are any computing task that, when executing, require one or both of:CPU utilization and memory consumption. Scheduled computing tasks suchas scheduled computing task 106 are computing tasks that are scheduledto be executed either automatically or manually for events such as ascheduled meeting, software update, computer backup, etc. Computingefficiency program 104 checks schedules of various applications thatschedule computing tasks such as computing task 106. For example,computing efficiency program 104 will check calendar programs formeetings that involve a computing task such as computing task 106.

In step 208, computing efficiency program 104 estimates the CPUutilization and memory consumption of unscheduled computing task 108. Invarious embodiments, computing efficiency program 104 estimates the CPUutilization and memory consumption of unscheduled computing task 108 bysearching for computing tasks that are substantially similar in database110 where the substantially similar computing tasks have knownparameters (i.e., one or both of: the CPU utilization, memoryconsumption). The operational processes involved in computing efficiencyprogram 104 estimations of unscheduled computing task 108 parameters arediscussed in more detail in FIG. 4.

In step 210, computing efficiency program 104 estimates the CPUutilization and memory consumption of scheduled computing task 106. Invarious embodiments, computing efficiency program 104 estimates the CPUutilization and memory consumption of scheduled computing task 106 bysearching for computing tasks that are substantially similar in database110 where the substantially similar computing tasks have knownparameters (i.e., one or both of: the CPU utilization, memoryconsumption). The operational processes involved in computing efficiencyprogram 104 estimations of scheduled computing task 106 parameters arediscussed in more detail in FIG. 4.

In step 212, computing efficiency program 104 warns a user if thecombined CPU utilization and memory consumption of unscheduled computingtask 108 and the one or more scheduled computing tasks such as scheduledcomputing task 106 exceed a given threshold. For example, when CPUutilization exceeds 70%, the user may experience significant lag.Computing efficiency program 104 estimates that this situation willoccur if the user opens or executes unscheduled computing task 108 priorto one or more scheduled computing tasks such as scheduled computingtask 106.

FIG. 3 illustrates a first part of operational processes, generallydesignated 300, for estimating computing resource consumption bycomputing efficiency program 104, in accordance with an exemplaryembodiment of the present invention.

In step 302, computing efficiency program 104 optionally determines thatscheduled computing task 106 is scheduled to occur within a specifiedtime from the unscheduled computing task. This optional step allows auser or administrator to save CPU utilization and memory consumption byonly executing computing efficiency program 104 when a unscheduledcomputing task such as unscheduled computing task 108 and a scheduledcomputing task such as scheduled computing task 106 are likely tooverlap with a certain probability. In various embodiments, this step isperformed if the user or administrator sets a time constraint whereby ascheduled computing task such as scheduled computing task 106 must bescheduled to be initiated less than a specified amount of time in thefuture. This optional step causes computing efficiency program 104 tonot proceed if no scheduled computing tasks such as scheduled computingtask 106 are scheduled to occur before the specified amount of time.

In step 304, computing efficiency program 104 analyzes unscheduledcomputing task 108 for identifying attributes. Identifying attributesinclude, for example, file size, file type, programming language used,etc. In general, identifying attributes are metadata that are analyzedby computing efficiency program 104 to show correlations regarding theamount of CPU utilization, memory consumption, and execution time of afirst unscheduled computing task relative to a second unscheduledcomputing task. In various embodiments, efficiency program 104 containsstatistical subroutines that search for correlations between certaintypes of metadata in various unscheduled computing tasks and the amountof CPU and memory resources the unscheduled computing tasks consume aswell as execution time. For example, efficiency program 104 investigateswhether there is a correlation between file size and memory consumptionfor unscheduled computing tasks of a specific file type. Usingstatistical analysis, efficiency program 104 determines that there issuch a correlation for unscheduled computing tasks of that specific filetype and consequently uses file size as an identifying attribute forestimating memory consumption for unscheduled computing tasks of thatparticular file type.

In step 306, computing efficiency program 104 searches database 110 forone or more computing task(s) that are substantially similar tounscheduled computing task 108. In various embodiments, “substantiallysimilar” indicates that metadata contained in the one or more computingtask(s) found by computing efficiency program 104 will allow acorrelation to be made between the consumption of computer resources bythose one or more computer task(s) and the consumption of computerresources by unscheduled computing task 108.

In decision 308, computing efficiency program 104 determines whether oneor more computer task(s) substantially similar to unscheduled computingtask 108 have been identified in database 110. If no substantiallysimilar computer tasks have been found (i.e., “N”), then computingefficiency program 104 proceeds to step 310. If one or moresubstantially similar computer tasks have been found (i.e., “Y”), thencomputing efficiency program 104 proceeds to step 314.

In step 310, computing efficiency program 104 optionally warns a user ofa possible conflict with scheduled computing task 106 if the userchooses to execute unscheduled computing task 108 at that time. Inexemplary embodiments, computing efficiency program 104 provides theoptional warning in step 310 only if computing efficiency program 104has optionally determined that scheduled computing task 106 is scheduledto occur within a specified time from unscheduled computing task 108 instep 302. The warning that is output by computing efficiency program 104in step 310 indicates a conflict could occur between unscheduledcomputing task 108 and scheduled computing task 106, but there is nostatistical data to indicate the probability of this conflict happening.

In step 312, computing efficiency program 104 determines the CPUutilization, memory consumption, and execution time of unscheduledcomputing task 108 upon execution and stores this data in database 110along with identifying attributes of unscheduled computing task 108. Theidentifying attributes of unscheduled computing task 108 will allowcorrelation of the unscheduled computing task 108 CPU utilization,memory consumption, and execution time with future substantially similarunscheduled computing tasks. These correlations will lead to estimatesof the future unscheduled computing tasks in terms of CPU utilization,memory consumption, and execution time.

In step 314, computing efficiency program 104 estimates the executiontime of unscheduled computing task 108 based on correlation of one ormore identifying attributes of unscheduled computing task 108 and one ormore identifying attributes of substantially similar computing tasksfound in the search of database 110 in step 306. For example, computingefficiency program 104 uses statistical analysis to determine that thereis a correlation between file sizes and execution time for unscheduledcomputing tasks of a particular programming language. In step 314,computing efficiency program 104 uses that correlation, at least inpart, to estimate the execution time of unscheduled computing task 108.

In decision 316, computing efficiency program 104 determines whether theexecution time of unscheduled computing task 108 overlaps with ascheduled computing task such as scheduled computing task 106. Computingefficiency program 104 checks the unscheduled computing task 108execution time window to determine whether a scheduled computing tasksuch as scheduled computing task 106 is scheduled to begin beforeunscheduled computing task 108 is through executing. If computingefficiency program 104 determines there will be no overlap betweenunscheduled computing task 108 and a scheduled computing task such asscheduled computing task 106 (i.e., “Y”), then the user is not warned.When unscheduled computing task 108 is executed, computing efficiencyprogram 104 determines the CPU utilization, memory consumption, andexecution time of unscheduled computing task 108 and stores this data indatabase 110 along with unscheduled computing task 108 identifyingattributes (i.e., step 312). If computing efficiency program 104determines there will be an overlap between unscheduled computing task108 and a scheduled computing task such as scheduled computing task 106(i.e., “N”), then computing efficiency program 104 continues to off-pagereference 318, i.e., the operational processes 400 described in FIG. 4.

FIG. 4 illustrates a second part of operational processes, generallydesignated 400, for estimating computing resource consumption bycomputing efficiency program 104, in accordance with an exemplaryembodiment of the present invention.

In step 402, computing efficiency program 104 estimates one or both of:the CPU utilization and memory consumption of unscheduled computing task108. By determining correlations between unscheduled computing task 108identifying attributes and substantially similar identifying attributesof computing tasks stored in database 110, computing efficiency program104 estimates one or both of: the CPU utilization and memory consumptionof unscheduled computing task 108 from the known CPU utilization andmemory consumption of the reference computing tasks found in step 306(FIG. 3).

In step 404, computing efficiency program 104 analyzes scheduledcomputing task 106 for identifying attributes. For example, identifyingattributes include file size, file type, programming language used, etc.In general, identifying attributes are metadata that allow correlationsregarding the amount of CPU utilization, memory consumption, andexecution time of a first scheduled computing task relative to a secondscheduled computing task. In various embodiments, efficiency program 104contains statistical subroutines that search for correlations betweencertain types of metadata in various scheduled computing tasks and theamount of CPU and memory resources the scheduled computing tasksconsume. For example, efficiency program 104 investigates whether thereis a correlation between file size and memory consumption for scheduledcomputing tasks of a specific file type. Using statistical analysis,efficiency program 104 determines that there is such a correlation forscheduled computing tasks of that specific file type and consequentlyuses file size as an identifying attribute for estimating memoryconsumption for scheduled computing tasks of that specific file type.

In step 406, computing efficiency program 104 searches database 110 forone or more computing task(s) that are substantially similar toscheduled computing task 106. In various embodiments, “substantiallysimilar” indicates that metadata contained in the one or more computingtask(s) found by computing efficiency program 104 will allow acorrelation to be made between the consumption of computer resources bythose one or more computer task(s) and the consumption of computerresources by scheduled computing task 106.

In decision 408, computing efficiency program 104 determines whether oneor more computer task(s) substantially similar to scheduled computingtask 106 have been identified in database 110. If no substantiallysimilar computer tasks have been found (i.e., “N”), then computingefficiency program 104 proceeds to step 410. If one or moresubstantially similar computer tasks have been found (i.e., “Y”), thencomputing efficiency program 104 proceeds to step 414.

In step 410, computing efficiency program 104 optionally warns a user ofa possible conflict with scheduled computing task 106 if the userchooses to execute unscheduled computing task 108 at that time. Theoptional warning is output by computing efficiency program 104 toindicate that unscheduled computing task 108 will overlap with scheduledcomputing task 106. However, without an ability to estimate the CPUutilization and memory consumption of scheduled computing task 106,computing efficiency program 104 cannot estimate whether the combinedCPU utilization and memory consumption of both unscheduled computingtask 108 and scheduled computing task 106 will exceed a specifiedthreshold (decision 416, vide infra). In various embodiments, theoptional warning in step 410 depends on the amount of CPU utilizationand memory consumption estimated by computing efficiency program 104 instep 402. Thus, if the CPU utilization and memory consumption ofunscheduled computing task 108 is estimated to exceed a secondarythreshold that is lower than the specified threshold in decision 416,the optional warning in step 410 is triggered even if the CPUutilization and memory consumption of scheduled computing task 106cannot be estimated by computing efficiency program 104. In exemplaryembodiments, the secondary threshold that triggers the optional warningin step 410 is automatically set as a fractional amount of the specifiedthreshold in decision 416.

In step 412, computing efficiency program 104 determines the CPUutilization, memory consumption, and execution time of unscheduledcomputing task 108 and scheduled computing task 106 upon theirexecution. Computing efficiency program 104 stores this data in database110 along with identifying attributes of unscheduled computing task 108and scheduled computing task 106. The identifying attributes ofunscheduled computing task 108 and scheduled computing task 106 willallow correlation of their CPU utilization, memory consumption, andexecution time with future substantially similar unscheduled computingtasks and scheduled computing tasks. These correlations will lead toestimates of the future unscheduled/scheduled computing tasks in termsof CPU utilization, memory consumption, and execution time.

In step 414, computing efficiency program 104 estimates the CPUutilization and memory consumption of scheduled computing task 106. Bydetermining correlations between scheduled computing task 106identifying attributes and substantially similar identifying attributesof computing tasks stored in database 110, computing efficiency program104 estimates the CPU utilization and memory consumption of scheduledcomputing task 106 from the known CPU utilization and memory consumptionof the reference computing tasks found in step 406.

In step 416, computing efficiency program 104 determines whetheroverlapping execution of unscheduled computing task 108 and scheduledcomputing task 106 will exceed a specified threshold of one or both of:CPU utilization and memory consumption. Exceeding the specifiedthreshold creates, for example, lag time or an abnormal end to one orboth programs. If the specified threshold is not exceeded (i.e., “N”),computing efficiency program 104 continues to step 412. If the specifiedthreshold is exceeded (i.e., “Y”), computing efficiency program 104warns the user in step 418. Regardless of the decision the user makesregarding the step 418 warning, when unscheduled computing task 108 andscheduled computing task 106 have been executed, computing efficiencyprogram 104 will record one or more of: the CPU utilization, memoryconsumption, and execution time of one or both of unscheduled computingtask 108 and scheduled computing task 106 in step 412.

FIG. 5 depicts a block diagram, 500, of components of computing device102, in accordance with an illustrative embodiment of the presentinvention. It should be appreciated that FIG. 5 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be made.

Computing device 102 includes communications fabric 502, which providescommunications between computer processor(s) 504, memory 506, persistentstorage 508, communications unit 510, and input/output (I/O)interface(s) 512. Communications fabric 502 can be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system. For example, communications fabric502 can be implemented with one or more buses.

Memory 506 and persistent storage 508 are computer-readable storagemedia. In this embodiment, memory 506 includes random access memory(RAM) 514 and cache memory 516. In general, memory 506 can include anysuitable volatile or non-volatile computer-readable storage media.

Computing efficiency program 104, scheduled computing task 106,unscheduled computing task 108, and database 110 are stored inpersistent storage 508 for execution and/or access by one or more of therespective computer processors 504 via one or more memories of memory506. In this embodiment, persistent storage 508 includes a magnetic harddisk drive. Alternatively, or in addition to a magnetic hard disk drive,persistent storage 508 can include a solid state hard drive, asemiconductor storage device, read-only memory (ROM), erasableprogrammable read-only memory (EPROM), flash memory, or any othercomputer-readable storage media that is capable of storing programinstructions or digital information.

The media used by persistent storage 508 may also be removable. Forexample, a removable hard drive may be used for persistent storage 508.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer-readable storage medium that is also part of persistent storage508.

Communications unit 510, in these examples, provides for communicationswith other data processing systems or devices, including resources ofnetwork 112. In these examples, communications unit 510 includes one ormore network interface cards. Communications unit 510 may providecommunications through the use of either or both physical and wirelesscommunications links. Computing efficiency program 104, scheduledcomputing task 106, unscheduled computing task 108, and database 110 maybe downloaded to persistent storage 508 through communications unit 510.

I/O interface(s) 512 allows for input and output of data with otherdevices that may be connected to computing device 102. For example, I/Ointerface 512 may provide a connection to external devices 518 such as akeyboard, keypad, a touch screen, and/or some other suitable inputdevice. External devices 518 can also include portable computer-readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data used to practiceembodiments of the present invention, e.g., computing efficiency program104, scheduled computing task 106, unscheduled computing task 108, anddatabase 110, can be stored on such portable computer-readable storagemedia and can be loaded onto persistent storage 508 via I/O interface(s)512. I/O interface(s) 512 also connect to a display 520.

Display 520 provides a mechanism to display data to a user and may be,for example, a computer monitor, or a television screen.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

It is to be noted that the term(s) such as “Smalltalk” and the like maybe subject to trademark rights in various jurisdictions throughout theworld and are used here only in reference to the products or servicesproperly denominated by the marks to the extent that such trademarkrights may exist.

What is claimed is:
 1. A computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on at least one of the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to determine that a user is attempting to execute an unscheduled computing task; program instructions to estimate a length of time of execution for the unscheduled computing task; program instructions to determine that a scheduled computing task is scheduled to execute while the unscheduled computing task is executing, wherein the scheduled computing task is scheduled to be executed automatically, wherein the scheduled computing task occurs during an event scheduled in a calendar program, a software update, and a computer backup; program instructions to warn the user that the unscheduled computing task will be executing when the scheduled computing task begins executing; program instructions to estimate a utilization of processing and a memory consumption for the unscheduled computing task and the scheduled computing task; program instructions to determine whether the utilization of processing and the memory consumption for the the unscheduled computing task and the scheduled computing task exceed a threshold; in response to a determination that the threshold will be exceeded, program instructions to warn the user that the threshold will be exceeded; program instructions to analyze the unscheduled computing task and the scheduled computing task for one or more first identifying attributes; program instructions to search a database for one or more stored computing tasks that have one or more second identifying attributes; program instructions to identify a predictive correlation between at least one of the one or more first identifying attributes and at least one of the one or more second identifying attributes, wherein the predictive correlation allows an estimate to be made of the utilization of processing and the memory consumption and wherein the one or more first identifying attributes and the one or more second identifying attributes include a file size, a file type, and a program language used, and the length of time of execution for the unscheduled computing task and the scheduled computing task. 